Digital Commons Network^™

Advancing Electrical Stimulation: Full-Head Mri Segmentation For Abnormal Brain Anatomy With Tdcs, Andrew Birnbaum

Dissertations and Theses

Evaluating the effectiveness of transcranial direct current stimulation (tDCS) is essential for guiding its integration into therapeutic and performance-enhancement applications. In our laboratory, we investigate the efficacy of tDCS across multiple experimental models, including both animal and human studies. I have contributed significantly to the execution and analysis of these experiments, which include studies in rats and healthy human participants aimed at evaluating whether electrical stimulation of the motor cortex can enhance motor learning. These studies assess improvements in fine motor performance resulting from tDCS. In stroke patients, I contribute to our investigation of tDCS as a rehabilitative intervention, particularly …

Wearable Disposable Elecetrotherapy, Mohamad Fallahrad

Dissertations and Theses

Non-invasive electrotherapies offer promising treatments for a wide range of conditions such as pain, headaches, depression, addiction, cognitive decline, wound healing, and drug delivery. However, patient compliance remains low due to the high initial cost, cumbersomeness and inconvenience of existing technology compared to pharmaceuticals. Current electrotherapy devices are often bulky and require users to connect disposable electrodes, initiate programs, and manage charging cycles, which hinders widespread adoption.

We address these challenges by designing and validating a novel electrotherapy platform that is single-use, disposable, low-cost, and wearable. Activated automatically upon skin contact, the device delivers a preset dose of controlled electrical …

An Environmental And Durability Study Of Bonded Structural Patch Repairs With Finite Element And Machine Learning Enabled Predictions, Yesim Kokner

Dissertations and Theses

Aircraft and vehicles experience substantial structural and aerodynamic stresses over their operational lifetimes. These stresses can cause damage or structural weakening, especially in aging military and civilian aircraft and vehicles. Depending on the severity of the damage, three options are available to alleviate the damage in these structures or parts: complete replacement of the aircraft or vehicle, replacement of the damaged part, or temporary repair of the damage.

The goal of this study is to evaluate damaged specimens repaired with an adhesively bonded patch subjected to quasi-static and fatigue loads under various environmental conditions. The patch repair technique is widely …

Development Of An Quadcopter Unmanned Aerial Vehicle For Atmospheric Remote Sensing, Omar J. Addasi

Dissertations and Theses

This paper explores the development of a quadcopter unmanned aerial vehicle (UAV, a.k.a. drone) for atmospheric remote sensing of temperature, pressure, humidity, and PM2.5 particulate matter quantities. A 3-D printed drone body is designed and flight tuning is performed. An optimal length for an upward extending mast for the drone body is determined. Low cost, lightweight sensors are compared against higher precision sensors in both static and dynamic conditions. In addition, an initial investigation into the design of a pressure sensor based anemometer is performed.

From Tpu To Qpu: Bridging Fidelity Gaps Across Next-Generation Computing Systems, Mohammad Walid M. Charrwi

Dissertations and Theses

Modern computing systems continue to advance rapidly, enabling unprecedented computational capabilities across diverse domains. Among these powerful architectures are AI accelerators such as Tensor Processing Units (TPUs) and quantum computing systems utilizing Quantum Processing Units (QPUs) stand out as trans-formative technologies. Despite their potential, these systems share significant challenges related to hardware infidelity, manifested as error-induced degradation in computational accuracy and reliability. This thesis explicitly addresses cost-effective methods to screen-out defective AI accelerators across next-generation computing architectures and boost quantum circuit output fidelity through hierarchical circuit optimization using advanced machine learning methodologies.

This thesis first proposes a cost-effective testing methodology …

Renewable Energy Integration In Nyc Subway: Solar Panels (Under Railroads And At The Subway's Edge) & Vertical Axis Wind Turbines (Vawts) Near Tracks, Pengdwinde Olivier Saba

Dissertations and Theses

As urban populations continue to expand, the demands on public transit systems in densely populated regions like New York City are escalating. Multiple cities face the dual challenge of increasing ridership and the imperative to minimize their environmental footprints.According to Law 97 in NYC, the goal is to reduce emissions by 40% and to reach net zero by 2050. An innovative solution will need to be integrated into the NYC environment, such as the subway system, where there are a potential unuse space, building rooftop, since we know that spaces in New York City are very critical, such as these …

Design And Lab Implementation Of An Air Source Transcritical Co2 Heat Pump, Geoffrey Turbeville

Dissertations and Theses

A laboratory-scale air-source transcritical CO2 heat pump (TCHP) was developed to evaluate the performance of low-global-warming-potential (GWP) refrigerants for cold climate applications. A custom climate chamber was also constructed to simulate winter weather conditions typical of the northeastern United States. Both the TCHP and the chamber were fully instrumented to collect temperature, pressure, and mass flow data, which were used to calculate the co- efficient of performance (COP) in accordance with ASHRAE standard refrigerant enthalpy methods. Prior to testing the CO2 system, the experimental setup was benchmarked using a commercially available R410A heat pump manufactured by LG.

The climate chamber …

A Novel Dual-Imaging Approach For Visualizing Multiphase And Droplet Interactions Including Shock-Driven Flows, Tad Jerzy Misztal

Dissertations and Theses

Shock-droplet/particle interactions have garnered substantial interest in recent years, fueled by advancements in aerospace and defense technologies, including supersonic and hypersonic systems in highly humid conditions, as well as the ongoing space exploration efforts from global space centers as well as private space companies. Understanding the interactions between shockwaves and droplets that impact on solid surfaces is critical due to the potential to cause significant damage to materials and structures in high-speed flow environments. Studies like these have applications in areas ranging from aerospace engineering to blast mitigation systems, where these interactions play a pivotal role in designing the relevant …

Experimental Characterization Of Heat Transfer And Fluid Flow In Tcr Fuel Elements Under Varying Operational Conditions, El Mokhtar Majdoub Em

Dissertations and Theses

ABSTRACT

The Transformational Challenge Reactor (TCR) marks a significant leap forward in nuclear reactor innovation, focusing on modular construction, high efficiency, and improved safety. This research explores the coupled behavior of heat transfer and fluid flow within the TCR's 3D-printed ceramic core under varying operational conditions. Nitrogen was utilized as the cooling medium, with experiments carried out at pressures ranging from 300 to 600 psi and temperatures spanning 100°C to 300°C. Critical parameters, including inlet and outlet gas temperatures, wall temperatures at both ends of the core, and coolant flow rates were monitored to evaluate thermal performance and system reliability. …

Virtual Environment Creation And Camera Calibration For Soft Target Identification And Assistance In Crowded Spaces With A Sensor Network And A Robotic Dog, Eltan Samoylov

Dissertations and Theses

Crowded places are increasingly targets of violence due to the increased accessibility and covertness of weapons, explosives, and other technology like drones. Addressing the challenges of protecting crowded places and assisting vulnerable individuals requires a multidisciplinary approach, taking inspiration from many different perspectives. Video surveillance of these crowded public facilities, such as train and bus stations, airports, shopping malls, and sports arenas, is very important to public safety, both for identifying threats/terrorist attacks and implementing evacuation plans.

The work of this thesis is part of a larger project aiming to explore the potential of using real-time computer vision and deep …

Cfd Modeling And Simulation Of Natural Circulation In Helium- Cooled Very High Temperature Reactors, Mohammad Sakib U. Abrar

Dissertations and Theses

This thesis investigates the thermal-hydraulic behavior of natural circulation in helium-cooled Very High Temperature Reactor (VHTR) systems, focusing on the performance and validation of passive safety features under Pressurized or Depressurized Loss of Forced Cooling (P-LOFC or D-LOFC) events. An experimental facility inspired by the General Atomics 350 MWt Modular High Temperature Gas-Cooled Reactor (MHTGR) was developed at The City College of New York. The setup consists of a plenum-to-plenum flow loop with four riser and four downcomer tubes, each equipped with heating coils, thermocouples, and pressure sensors. Natural circulation is driven by density gradients induced by asymmetric heating of …

Classification Of Variable Stars Using Convolutional Neural Network, Abhina Premachandran Bindu

Dissertations and Theses

This research focuses on developing Convolutional Neural Networks (CNNs), for the process of classifying and identifying variable stars through the analysis of unprocessed light curves from Transiting Exoplanet Survey Satellite (TESS). As astronomical data is becoming increasingly complex, and as advanced missions deploy sophisticated instruments for data collection, both the quality and quantity of the data are improving at a rapid pace. This has created an urgent need to automate the analysis process using efficient and effective methods, such as those based on machine learning. While previous research has explored machine learning approaches, there has been limited focus on implementing …

Characterization Of The Intrinsic Neural Timescale Indices As A Reliable Fingerprint Of Brain Dynamics, Helya Honarpisheh

Dissertations and Theses

Intrinsic neural timescales (INTs) characterize the persistence of neural activity over time and offer insight into the brain’s temporal hierarchy. This thesis evaluates and compares six autocorrelation-based INT metrics—AR(1) Coefficient (Autoregressive Coefficient at 1), First Zero Lag, Lag at ACF = 1/e, Sum of Positive ACFs, ACF at Half Lag, Exponential Decay Constant (τ)— using resting-state fMRI data from 400 cortical regions across a large, lifespan sample (ages 6– 85) from the NKI-Rockland dataset. A discriminability analysis revealed that the AR(1) coefficient provided the highest test-retest reliability and individual specificity across repeated scans, establishing it as the most reliable INT …

Metasurfaces And Their Applications In Photonic Devices, Shuwei Guo

Dissertations and Theses

Metasurfaces are flat artificial optical elements composed of dielectric and/or metallic nanostructures. They can manipulate light in unprecedented ways by altering amplitude, phase, and polarization at subwavelength scales. The ability of these two-dimensional elements to perform multiple optical functions within compact optical systems—while offering high functionality, small form factors, and easy integration into optoelectronic devices—has sparked significant interest across various fields and industries. These applications span imaging, sensing, nonlinear and quantum optics, optical computing, automotive technology, augmented and virtual reality, and more.

In this dissertation, we explore and design new multifunctional metasurfaces with a focus on manipulating spectral responses. First, …

Using Deep Neural Nets In Writer Identification & Analysis, Aditya Majithia

Dissertations and Theses

This thesis focuses on developing automated deep learning methods for writer identification and writer attribute prediction from handwriting. It introduces two novel architectures: Convolutional Transformer Encoder (CTE) and Convolutional Swin Encoder (CSE). CTE is designed for determining authorship from handwritten text, be it modern or historical handwriting. CTE tracks subtle features and cues from handwriting strokes to distinguish authorship. It is the first of its kind capable to operate on historical handwritten fragments, setting it apart from existing methods that rely on entire document pages. CSE is designed to determine multiple attributes of an author such as authorship, gender, age …

Utilizing Deep Learning Audio Models For Blind And Low Vision Crosswalk Assistance, Wayne Lam

Dissertations and Theses

Navigating urban environments poses significant challenges for blind and low vision (BLV) individuals, particularly at street intersections where determining when it is safe to cross can be life-threatening. In New York City, where pedestrian fatalities are on the rise and only 2% of intersections are equipped with Accessible Pedestrian Signals (APS), alternative solutions are urgently needed. This thesis proposes an audio-based deep learning approach to support BLV individuals at crosswalks by detecting traffic movement direction and idling states using spatial sound. With 4-channel audio capturing capabilities of wearables, such as Meta Project Aria glasses, we explore state-of-the-art sound event localization …

Cognitive Map Generation For Vision And Language Navigation, Alexander Sandoval Mesa

Dissertations and Theses

Visual-Language Navigation (VLN) presents significant challenges for autonomous agents, such as robots and virtual assistants, particularly in complex, dynamic environments where the seamless integration of visual perception and natural language understanding is critical. Traditional VLN systems often struggle with effectively aligning language instructions and visual scene understanding, limiting their adaptability and navigation efficiency.

This thesis proposes a novel Cognitive Map-based framework that addresses these challenges by transforming natural language navigation instructions into structured graph representations. The Cognitive Map consists of nodes representing waypoints, landmarks, decision points, and edges encoding spatial relationships and navigational actions. These maps are generated using Large …

Multi-Material Adhesive Bonded Joints Under Static And Dynamic Loading, Gizem Derya Demir

Dissertations and Theses

Adhesively bonded joints present significant potential for reducing structural weight and enhancing performance in modern and future engineering structures. By enabling the elimination or reduction of traditional mechanical fasteners and facilitating the integration of dissimilar materials, adhesives can contribute to more efficient, lightweight designs. However, to fully leverage these benefits—especially in high-performance applications—adhesive materials must exhibit robust behavior under both static and dynamic loading conditions, such as ballistic impact. Despite their promise, the failure mechanisms of adhesives under such high-strain-rate scenarios remain insufficiently understood.

This dissertation investigates the performance of adhesively bonded multi-material joints subjected to static loading and ballistic …

Data Driven Bridge Deck Deterioration Modeling And Maintenance Intervention Scheduling, Deepak Kumar

Dissertations and Theses

Majority of over 617,000 bridges across the United States are significantly impacted by environmental factors, aging materials, and heavy traffic loads. According to the 2021 Infrastructure Report, nearly 231,000 bridges require repair or preservation work, with 46,154 (7.5%) being classified as structurally deficient, thereby posing risks for mor than 178 million daily trips across these bridges. Despite recent improvements, 42% of U.S. bridges are at least 50 years old, underscoring an urgent need for increased investment to meet repair demands. The nation’s backlog of bridge repairs is estimated at $125 billion, with a 58% increase in annual spending required to …

Generation And Characterization Of Human Blood-Brain Barrier Models For Investigating Neuropsychiatric Disorders And Tumor Metastasis, Yunfei Li

Dissertations and Theses

The blood–brain barrier (BBB) is important in the normal function of the central nervous system (CNS). An altered BBB has been described in various neuropsychiatric disorders. The brain-specific microvascular endothelial cell (BMEC) is an essential structural component of the BBB. To test if integrity of the BBB formed by BMECs is compromised in 22q11.2 deletion syndrome (also called DiGeorge syndrome), which is one of the validated genetic risk factors for schizophrenia, a 2D iBBB (induced BBB) on a Transwell filter was generated from human microvascular endothelial cells (HBMECs) derived from the induced pluripotent stem cells (iPSCs) out of patients with …

Experimental And Analytical Investigation Of Particle Dynamics In Newtonian And Non-Newtonian Fluids In A Taylor-Couette Cell, Andres F. Velez Mendoza

Dissertations and Theses

This doctoral dissertation investigates heavy particle sedimentation in Newtonian and non-Newtonian fluids, aiming to understand their behavior in Drilling Fluid (DF) systems used in oil and gas industry, where such phenomenon can lead to operational issues such as lost circulation, well control problems, and even blowouts. To simulate DF dynamics under operational conditions, this study utilizes a Taylor-Couette (TC) cell, which consists of a rotating inner cylinder and a stationary outer cylinder separated by a 9.0 mm annular gap. The TC cell allows for the investigation of the sedimentation behavior of spherical particles within both Newtonian fluids (deionized water and …

Deep Learning Architectures For Improving Weather Research And Forecasting (Wrf) Precipitation Estimates And Landslide Susceptibility Mapping: A Case Study Of Puerto Rico, Said A. Mejia Manrique

Dissertations and Theses

Precipitation is a critical factor in the Earth’s hydrological cycle and has a profound impact on various environmental and socioeconomic systems, including management of water resources, flood forecasting, and the evaluation of natural hazards, particularly those associated with rainfall-induced landslides. For the latter, obtaining precise precipitation estimates is essential, as intense rainfall events can trigger landslides that pose significant risks to human life, infrastructure, and ecosystems, particularly in mountainous regions. Puerto Rico (PR), with its mountainous terrain, tropical climate, and vulnerability to hurricanes, provides a unique environment for studying precipitation patterns and the need for accurate rainfall estimates. The complex …

An Exploration Of Object Representations And Defense Mechanisms In Caregiver-Child Dyads On The Thematic Apperception Test, Hannah L. Bloom

Dissertations and Theses

Caregiver-child interactions, beginning in infancy, are essential for socio-emotional development. Through these exchanges, caregivers impart fantasies, fears, and beliefs—both consciously and unconsciously—that shape the child’s internal models of self and others (object representations) and strategies for managing intense emotions (defense mechanisms). Historically, projective tests, such as the Thematic Apperception Test (TAT), have been used to explore these constructs. In the TAT, participants craft narratives based on images that portray characters in different emotional states and interpersonal situations. Through their responses, participants project elements of their own internal world into the stories they create. Despite the TAT’s success in differentiating diagnostic …

A Message From The President

Bulletin of the Ninth District Dental Association

A regular column from the president of the Ninth District of New York bringing the latest news to the membership.

A Message From The President

Bulletin of the Ninth District Dental Association

A regular column from the president of the Ninth District of New York bringing the latest news to the membership.

A Message From The President

Bulletin of the Ninth District Dental Association

A regular column from the president of the Ninth District of New York bringing the latest news to the membership.

Antibiotic-Resistant Nontyphoidal Salmonella And Campylobacter Isolates Associated With International Travel, Connecticut 2010 – 2023, Shilpa Mudumbe

Public Health Theses

Antibiotics are helpful for limiting duration and complications of Salmonella andCampylobacter isolates in selected age groups and people who are immunosuppressed. However, antibiotic-resistant (AR) foodborne pathogens have been on the rise in the United States over the past 10 years and are often linked to international travel (IT). Long-term trends on AR have not been examined in Connecticut (CT). This study evaluates trends in AR among nontyphoidal Salmonella and Campylobacter isolates in CT from 2010 to 2023 and examines the association between AR and IT. Data from submission of annual systematic samples of CT Salmonella and Campylobacter isolates to the …

Claude Ai And Literature Reviews: An Experiment In Utility And Ethical Use, Max Sparkman, Alan Witt

Milne Library

Generative large-language models (LLMs) such as ChatGPT and Claude have sparked debate throughout higher education about their potential and threats to the current pedagogical models for research. This paper scans the literature on the benefits and drawbacks of using LLMs in teaching and research, and compares and contrasts two literature reviews on the subject, one written by a human author and one produced by Claude. The comparison explores areas where the generative AI excels, such as quickly summarizing points of agreement across sources, as well as its limitations, like struggling with synthesis, providing incomplete citations, and hallucinating false information. While …

Message From The Ada President - Standing Up For Community Water Fluoridation, Brett Kessler

Bulletin of the Ninth District Dental Association

A message from ADA President Brett Kessler, D.D.S., regarding the importance of community water fluoridation.

A Hierarchical Bayesian Meta-Regression Model For Incorporating Exposure Range Variability, Xiaotong Xu

Public Health Theses

Accurately synthesizing evidence from epidemiologic studies is essential for understanding complex environmental risk relationships and establishing causal relationships. However, the majority of meta-analyses in this area ignore the possibility of variability in risk due to differences in study-specific exposure levels while typical dose-response statistical methods assume a single dose amount per study and not a distribution or range of doses (i.e., exposures). We develop a novel hierarchical Bayesian meta-regression framework that incorporates functional averaging over study-specific exposure ranges and models the underlying exposure-response relationship using a flexible Gaussian process. Using a low-rank predictive process formulation, our approach efficiently projects functional …